Showing papers on "Metropolitan area published in 2022"
TL;DR: Zhang et al. as mentioned in this paper used the PLUS model, which combines the Land use Expansion Analysis Strategy (LEAS) and the CA model, based on the multi-class random patch seed (CARS) model.
Abstract: Nowadays, cities meet numerous sustainable development challenges in facing growing urban populations and expanding urban areas. The monitoring and simulation of land use and land-cover change have become essential tools for understanding and managing urbanization. This paper interprets and predicts the expansion of seven different land use types in the study area, using the PLUS model, which combines the Land use Expansion Analysis Strategy (LEAS) and the CA model, based on the multi-class random patch seed (CARS) model. By choosing a variety of driving factors, the PLUS model simulates urban expansion in the metropolitan area of Hangzhou. The accuracy of the simulation, manifested as the kappa coefficient of urban land, increased to more than 84%, and the kappa coefficient of other land use types was more than 90%. To a certain extent, the PLUS model used in this study solves the CA model’s deficiencies in conversion rule mining strategy and landscape dynamic change simulation strategy. The results show that various types of land use changes obtained using this method have a high degree of accuracy and can be used to simulate urban expansion, especially over short periods.
72 citations
TL;DR: In this article , the authors analyzed the impact of land use/land cover change and its impact on the surface UHI intensity and urban thermal comfort using Landsat datasets and geographically weighted regression (GWR) in Delhi metropolitan city.
Abstract: The increasing urban heat island intensity (UHII)is a matter of concern for the sustainable urban planning and maintaining urban thermal comfort in the metropolitan cities of developing countries like India. Therefore, in the current research, the land use/land cover (LU/LC) change and its impact on the surface UHI intensity (SUHII) and urban thermal comfort has been analyzed using Landsat datasets and geographically weighted regression (GWR) in Delhi metropolitan city. The result shows that the built-up area has increased from 315.18 to 720.24 sq. km in Delhi during 1991 to 2018 while other LU/LC types have declined. This has resulted in a substantial increase in LST and SUHII. The minimum, maximum and mean SUHII has increased by 1.26 °C, 4.6 °C and 1.18 °C during 1991 to 2018 and hence, the thermal comfort has declined in the city. The GWR analysis showed that the performance of GWR model was very good in showing the association between LU/LC and SUHII and the LU/LC pattern has significant impact on SUHII. The outcome of this research can be utilized for the formulation of SUHI mitigation strategies and maintaining urban thermal comfort in Delhi and cities with similar geographical conditions. • SUHII and urban thermal comfort has been analyzed in response to changing LU/LC pattern in Delhi during 1991 to 2018. • The built-up area is doubled, whereas cropland decreased by half in Delhi during 1991 to 2018. • Mean SUHII has increased to about 1.18 °C in Delhi in last 27 years. • Urban thermal comfort has declined in Delhi because of increase in about 9 °C LST and 1.16 °C in SUHII in last 27 years. • The GWR model shows significant association (R 2 =0.48) between LU/LC and SUHII in Delhi.
61 citations
TL;DR: In this paper , the authors estimated the proportion of population living within 1, 2, 5, and 10 miles of a community pharmacy and quantified the role of chain vs regional franchises or independently owned pharmacies in providing access across degrees of urbanicity.
Abstract: Pharmacy accessibility is key for the emerging role of community pharmacists as providers of patient-centered, medication management services in addition to traditional dispensing roles.To quantify population access to community pharmacies across the United States.We obtained addresses for pharmacy locations in the United States from the National Council for Prescription Drug Programs and geocoded each. For a 1% sample of a U.S. synthetic population, we calculated the driving distance to the closest pharmacy using ArcGIS. We estimated the proportion of population living within 1, 2, 5, and 10 miles of a community pharmacy. We quantified the role of chain vs regional franchises or independently owned pharmacies in providing access across degrees of urbanicity.We identified 61,715 pharmacies, including 37,954 (61.5%) chains, 23,521 (38.1%) regional franchises or independently owned pharmacies, and 240 (0.4%) government pharmacies. In large metropolitan areas, 62.8% of the pharmacies were chains; however, in rural areas, 76.5% of pharmacies were franchises or independent pharmacies. Across the overall U.S. population, 48.1% lived within 1 mile of any pharmacy, 73.1% within 2 miles, 88.9% within 5 miles, and 96.5% within 10 miles. Across the United States, 8.3% of counties had at least 50% of residents with a distance greater than 10 miles. These low-access counties were concentrated in Alaska, South Dakota, North Dakota, and Montana.Community pharmacies may serve as accessible locations for patient-centered, medication management services that enhance the health and wellness of communities. Although chain pharmacies represent the majority of pharmacy locations across the country, access to community pharmacies in rural areas predominantly relies on regional franchises and independently owned pharmacies.
42 citations
TL;DR: In this article , the authors proposed an IoT based dynamic food supply chain for smart cities which not only ensures the food quality but also provides intelligent vehicle routing as well as tracing sources of contamination in FCM.
37 citations
18 Feb 2022
TL;DR: In this paper , the authors specify YANG data models and MIB modules that allow configuration and status reporting for bridges and end systems with the capabilities for Frame Replication and Elimination for Reliability (FRER) and Stream identification.
Abstract: This amendment specifies YANG data models and MIB modules that allow configuration and status reporting for bridges and end systems with the capabilities for Frame Replication and Elimination for Reliability (FRER) and Stream identification.
37 citations
TL;DR: In this paper, the authors proposed an IoT based dynamic food supply chain for smart cities which not only ensures the food quality but also provides intelligent vehicle routing as well as tracing sources of contamination in FCM.
37 citations
TL;DR: In this article , the authors compared arthropod, gastropod, and avian species richness and diversity between green and conventional roofs on neighbouring and identical buildings in metropolitan Sydney, Australia.
32 citations
TL;DR: In this article , the authors study the shape of Los Angeles metropolitan area with a permanent increase in working from home and find that workers who switch to telecommuting enjoy large welfare gains by saving commute time and moving to more affordable neighborhoods and that average real estate prices fall, with declines in core locations and increases in the periphery.
32 citations
TL;DR: In this paper, the authors compared arthropod, gastropod, and avian species richness and diversity between green and conventional roofs on neighbouring and identical buildings in metropolitan Sydney, Australia.
32 citations
TL;DR: In this article, the authors evaluated the impacts of ambient temperature and trip characteristics on the energy consumption of an electric vehicle (EV) during road tests and found that the EV specific energy consumption (SEC) increases under operation at low temperature, also showing a larger scatter.
31 citations
TL;DR: In this paper , the authors evaluated the impacts of ambient temperature and trip characteristics on the energy consumption of an electric vehicle (EV) during road tests and found that the EV specific energy consumption (SEC) increases under operation at low temperature, also showing a larger scatter.
TL;DR: Landscape functional zoning is used as a nexus to connect ES patterns and land use management and can provide references for conserving ESs and enhancing landscape sustainability in Beijing and other similar metropolitan areas worldwide.
TL;DR: In this article , the authors report the results of a Modified Delphi Approach (MDA) among experts about the future of urban tourism in a context of adaptation to climate change in Porto Metropolitan Area (Portugal), considering the outdoor thermal conditions perspective.
TL;DR: In this paper , the authors show that the COVID-19 pandemic brought house price and rent declines in city centers, and price increases away from the center, thereby flattening the bid-rent curve in most U.S. metropolitan areas.
TL;DR: In this paper , the authors developed a wastewater-based epidemiological model to track the evolution of the COVID-19 epidemic anywhere in the world where centralized water-based sanitation systems exist.
TL;DR: In this article , the relationship between landscape structure (landscape metrics) and land surface temperature (LST) across the spatial levels of UTE is explored. But the spatial hierarchy and interaction effects of the relationship among them are limitedly explored.
TL;DR: In this paper, the authors examined the spatial patterns of SARS-CoV-2 in sewage through a spatial sampling strategy across neighborhood-scale sewershed catchments and characterized the correlations between the sub-catchments over the sampling period.
TL;DR: In this paper , the authors analyzed urban policies impacts by quantifying built-up land, green spaces and their associated SUHI effects in the Lahore district of Pakistan using a tri-temporal medium resolution remote sensing imagery (2003, 2010 and 2019) and a long-term low resolution (1 km) Land Surface Temperature (LST) time series (2001-2020) to evaluate the impacts of the LULC changes on SUHI.
TL;DR: In this paper , an Artificial Neural Network (ANN) based Cellular Automata (CA) model is used to predict the LULC, seasonal LST, and urban thermal field variance (UTFVI) over Ahmedabad city, India using multi-date Landsat data.
Abstract: Rapid urbanization over the world's dense urban centers cause an enormous change in the land use land cover (LULC) over a metropolitan area, which adversely affects the land surface temperature (LST) and intensify the urban heat island phenomena. The present study emphasizes the prediction of LULC, seasonal LST, and urban thermal field variance (UTFVI) over Ahmedabad city, India using multi date Landsat data. Artificial Neural Network (ANN) based Cellular Automata (CA) model is use to predict the LULC, while the XGB Regression model is used to predict seasonal LST with input data from 2010, 2015, and 2020 to predict future scenarios of 2025 and 2030. The result suggests an addition in the built-up area of about 5.77% and 13.08%, while a deduction in cropland area of about 4.15% and 12.54% is manifest in the year 2025 and 2030, respectively. This excessive urban growth in the study area will cause to face higher LST ranges of greater than 45 °C (24.9 km 2 in 2025 and 24.2 km 2 in 2030) in summer and 35 °C (19.9 km 2 in 2025 and 43.6 km 2 in 2030) in winter. The concentration of higher LST zones is evident in the rural areas than urban areas, witnessing cool urban islands. The predicted LST analysis suggests a dominant occurrence of none UTFVI zone in the city area and the strongest UTFVI zone in the surrounding rural area during both the seasons. An increase in green space area and avoidance of non-impermeable surfaces is suggest in future scenarios to mitigate UHI. Furthermore, the outcome of the research can help urban planners and policymakers while formulating urban heat island related mitigation strategies in the near-future scenario. • ANN based Cellular Automata (CA) model is use to predict the future LULC with an overall accuracy of 89.2%. • XGB Regression model is used to predict seasonal LST with R 2 = 0.906, which is used to characterize SUHI. • More than 70% area in summer (>45 °C) and 40% in winter (>35 °C) would likely face higher LST zones. • Prevalence of None UTFVI zone in urban areas and the strongest UTFVI zone in the surrounding rural area.
TL;DR: In this paper , an integrated logistic multi-criteria evaluation (MCE) cellular automata (CA) Markov (logistic-MCE-CA-Markov) model and a geographic information system (GIS) were used to evaluate and predict the LULC changes.
TL;DR: In this article , the authors examined the spatial patterns of SARS-CoV-2 in sewage through a spatial sampling strategy across neighborhood-scale sewershed catchments and characterized the correlations between the sub-catchments over the sampling period.
TL;DR: In this article , the authors formalised the relationship between working from home and commuting by day of the week and time of day for two large metropolitan areas in Australia, Brisbane and Sydney, using a mixed logit choice model, identifying the influences on such choices together with a mapping model between the probability of working from homes and socioeconomic and other contextual influences that are commonly used in strategic transport models to predict demand for various modes by location.
Abstract: The need to recognise and account for the influence of working from home on commuting activity has never been so real as a result of the COVID-19 pandemic. Not only does this change the performance of the transport network, it also means that the way in which transport modellers and planners use models estimated on a typical weekday of travel and expand it up to the week and the year must be questioned and appropriately revised to adjust for the quantum of working from home. Although teleworking is not a new phenomenon, what is new is the ferocity by which it has been imposed on individuals throughout the world, and the expectation that working from home is no longer a temporary phenomenon but one that is likely to continue to some non-marginal extent given its acceptance and revealed preferences from both many employees and employ where working from home makes good sense. This paper formalises the relationship between working from home and commuting by day of the week and time of day for two large metropolitan areas in Australia, Brisbane and Sydney, using a mixed logit choice model, identifying the influences on such choices together with a mapping model between the probability of working from home and socioeconomic and other contextual influences that are commonly used in strategic transport models to predict demand for various modes by location. The findings, based on Wave 3 (approximately 6 months from the initial outbreak of the pandemic) of an ongoing data collection exercise, provide the first formal evidence for Australia in enabling transport planners to adjust their predicted modal shares and overall modal travel activity for the presence of working from home.
TL;DR: In this article , a multi-dimensional risk assessment strategy aided by the active participation of stakeholders is proposed to combat flood events for metropolitan cities in Turkey, which aims to prioritize the districts of Istanbul regarding flood hazard, flood vulnerability, and flood risk with a multilevel comprehensive decision-making procedure.
TL;DR: In this article , the impact of consumer-brand dyadic attributes (brand experience, brand resonance, brand trust, and consumer involvement) on the pursuit of luxury brands within the Indian context was studied.
TL;DR: In this paper, the authors formalised the relationship between working from home and commuting by day of the week and time of day for two large metropolitan areas in Australia, Brisbane and Sydney, using a mixed logit choice model, identifying the influences on such choices together with a mapping model between the probability of working from homes and socioeconomic and other contextual influences that are commonly used in strategic transport models to predict demand for various modes by location.
Abstract: The need to recognise and account for the influence of working from home on commuting activity has never been so real as a result of the COVID-19 pandemic. Not only does this change the performance of the transport network, it also means that the way in which transport modellers and planners use models estimated on a typical weekday of travel and expand it up to the week and the year must be questioned and appropriately revised to adjust for the quantum of working from home. Although teleworking is not a new phenomenon, what is new is the ferocity by which it has been imposed on individuals throughout the world, and the expectation that working from home is no longer a temporary phenomenon but one that is likely to continue to some non-marginal extent given its acceptance and revealed preferences from both many employees and employ where working from home makes good sense. This paper formalises the relationship between working from home and commuting by day of the week and time of day for two large metropolitan areas in Australia, Brisbane and Sydney, using a mixed logit choice model, identifying the influences on such choices together with a mapping model between the probability of working from home and socioeconomic and other contextual influences that are commonly used in strategic transport models to predict demand for various modes by location. The findings, based on Wave 3 (approximately 6 months from the initial outbreak of the pandemic) of an ongoing data collection exercise, provide the first formal evidence for Australia in enabling transport planners to adjust their predicted modal shares and overall modal travel activity for the presence of working from home.
TL;DR: In this article , a coupling coordination degree model was established with respect to the coordination degree of urbanization and the eco-environment based on panel data of three county-level cities and 14 counties in the Kashgar metropolitan area from 1999 to 2016.
TL;DR: Wang et al. as discussed by the authors quantitatively assessed the spatiotemporal distributions of multiple ecosystem services (ESs), from 1980 to 2017, based on land use changes and identified distinct ES bundles through the clustering method.
TL;DR: This paper examined the impact of the expansion of charters on racial segregation in public schools, defined using multiple measures of racial sorting and isolation, and found that charters modestly increase school segregation for Black, Hispanic, Asian, and White students.
Abstract: We examine the impact of the expansion of charter schools on racial segregation in public schools, defined using multiple measures of racial sorting and isolation. Our research design utilizes between-grade differences in charter expansion within school systems and an instrumental variables approach leveraging charter school openings. Charter schools modestly increase school segregation for Black, Hispanic, Asian, and White students. On average, charters have caused a 6 percent decrease in the relative likelihood of Black and Hispanic students being exposed to schoolmates of other racial or ethnic groups. For metropolitan areas, our analysis reveals countervailing forces, as charters reduce segregation between districts. (JEL I21, I24, J15)
TL;DR: In this paper , the authors used real-time, privacy-enhanced mobility data in the New York City, NY and Seattle, WA metropolitan areas to build a detailed agent-based model of SARS-CoV-2 infection to estimate the where, when, and magnitude of transmission events during the pandemic's first wave.
Abstract: Detailed characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission across different settings can help design less disruptive interventions. We used real-time, privacy-enhanced mobility data in the New York City, NY and Seattle, WA metropolitan areas to build a detailed agent-based model of SARS-CoV-2 infection to estimate the where, when, and magnitude of transmission events during the pandemic’s first wave. We estimate that only 18% of individuals produce most infections (80%), with about 10% of events that can be considered superspreading events (SSEs). Although mass gatherings present an important risk for SSEs, we estimate that the bulk of transmission occurred in smaller events in settings like workplaces, grocery stores, or food venues. The places most important for transmission change during the pandemic and are different across cities, signaling the large underlying behavioral component underneath them. Our modeling complements case studies and epidemiological data and indicates that real-time tracking of transmission events could help evaluate and define targeted mitigation policies.
TL;DR: Social determinants of geographic concentration of SARS-CoV-2 cases across 16 census metropolitan areas (hereafter, cities) in 4 Canadian provinces, British Columbia, Manitoba, Ontario and Quebec are quantified.
Abstract: Background: Understanding inequalities in SARS-CoV-2 transmission associated with the social determinants of health could help the development of effective mitigation strategies that are responsive to local transmission dynamics. This study aims to quantify social determinants of geographic concentration of SARS-CoV-2 cases across 16 census metropolitan areas (hereafter, cities) in 4 Canadian provinces, British Columbia, Manitoba, Ontario and Quebec. Methods: We used surveillance data on confirmed SARS-CoV-2 cases and census data for social determinants at the level of the dissemination area (DA). We calculated Gini coefficients to determine the overall geographic heterogeneity of confirmed cases of SARS-CoV-2 in each city, and calculated Gini covariance coefficients to determine each city’s heterogeneity by each social determinant (income, education, housing density and proportions of visible minorities, recent immigrants and essential workers). We visualized heterogeneity using Lorenz (concentration) curves. Results: We observed geographic concentration of SARS-CoV-2 cases in cities, as half of the cumulative cases were concentrated in DAs containing 21%–35% of their population, with the greatest geographic heterogeneity in Ontario cities (Gini coefficients 0.32–0.47), followed by British Columbia (0.23–0.36), Manitoba (0.32) and Quebec (0.28–0.37). Cases were disproportionately concentrated in areas with lower income and educational attainment, and in areas with a higher proportion of visible minorities, recent immigrants, high-density housing and essential workers. Although a consistent feature across cities was concentration by the proportion of visible minorities, the magnitude of concentration by social determinant varied across cities. Interpretation: Geographic concentration of SARS-CoV-2 cases was observed in all of the included cities, but the pattern by social determinants varied. Geographically prioritized allocation of resources and services should be tailored to the local drivers of inequalities in transmission in response to the resurgence of SARS-CoV-2.